Triple
T19874306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UN General Assembly resolution 38/161 |
E477600
|
entity |
| Predicate | hasDigitalObject |
P8017
|
FINISHED |
| Object | UN Official Document System record |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: UN Official Document System record | Statement: [UN General Assembly resolution 38/161, hasDigitalObject, UN Official Document System record]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDigitalObject Context triple: [UN General Assembly resolution 38/161, hasDigitalObject, UN Official Document System record]
-
A.
hasDigitalArchive
Indicates that an entity maintains or is associated with a collection of materials stored in a digital archive.
-
B.
hasDigitalForm
chosen
Indicates that something exists or is available in a digital or electronic format.
-
C.
hasDigitalObjectIdentifier
Indicates that an entity is associated with a specific Digital Object Identifier (DOI) that uniquely identifies it in a digital environment.
-
D.
hasDigitalLibrary
Indicates that an entity maintains or provides access to a collection of digital resources or publications.
-
E.
hasDigitalCollections
Indicates that an entity possesses or provides access to one or more collections of materials in digital form.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658d9ee108190a53cc6c8e115d0fa |
completed | April 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:51 p.m.